Fault Detection and Diagnostics for Rooftop Air Conditioners

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In order to reduce hardware costs, FDD for HVAC systems should use analytical
redundancy, which means the information from system measurements should be
preprocessed extensively before it is used to detect and diagnose faults. Furthermore, the
characteristics of being adaptive and generic and capable of handling multiplesimultaneous
faults should be emphasized when developing FDD for HVAC systems.
The rest of this chapter presents a literature review about FDD for HVAC systems
with emphasis on rooftop and other vapor compression air conditioners, provides the
motivation for the proposed research, summarizes the specific research objectives, and
discusses the general approach to evaluating the proposed FDD methods. Chapter 2
describes data sources used to validate and demonstrate the proposed approaches.
Chapters 3 and 4 describe the FDD methodology. Chapter 5 describes the economic
assessment. Chapter 6 summarizes the major completed work and provides some
recommendations for future work
1.2 Literature Review
1.2.1 Overview
In the late 1980’s, some researchers investigated common faults and methods for
fault detection and diagnosis in simple vapor compression cycles, such as a household
refrigerator. With the growing realization of the benefits brought by FDD, many more
papers about HVAC FDD have appeared in the last ten years. Figures 1-1 and 1-2 show
the paper statistics for HVAC FDD over the past 13 years.
From these two figures, it can be seen that the number of papers significantly
increased since 1996 and most of the papers focused on variable air volume (VAV) air
handling units (AHU). Since Comstock, Chen, and Braun (1999) did a very detailed and
comprehensive literature review in 1999, the next section of this report will briefly refer
to some significant contributions before 1999 and concentrate on up-to-date progress
after that.